{"id":"W4362658038","doi":"10.1002/sim.9734","title":"Point estimation for adaptive trial designs <scp>II</scp>: Practical considerations and guidance","year":2023,"lang":"en","type":"review","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"NIHR Cambridge Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Medical Research Council Canada; Department of Health and Social Care; Cancer Research UK; Health and Care Research Wales","keywords":"Estimation; Computer science; Point estimation; Point (geometry); Econometrics; Statistics; Mathematical optimization; Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01138245,0.0006344093,0.004233451,0.0003621955,0.0002344166,0.00004976671,0.000161562,0.0006338285,0.0000619628],"category_scores_gemma":[0.81541,0.0004997159,0.0001613927,0.0004485203,0.0008003408,0.00007026196,0.0001766914,0.001050239,0.00002440281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002124077,"about_ca_system_score_gemma":0.0007533566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001312186,"about_ca_topic_score_gemma":0.00003628535,"domain_scores_codex":[0.9918244,0.002287197,0.003714029,0.000894611,0.0007150955,0.0005647039],"domain_scores_gemma":[0.6038005,0.3941858,0.00111499,0.0004179365,0.0002842152,0.0001965433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002279124,0.0001380704,6.011793e-8,0.009090702,0.0002091949,0.0001158033,0.0001901262,0.000001100244,9.678866e-8,0.8022465,0.09175807,0.0960224],"study_design_scores_gemma":[0.009957608,0.002068339,5.119383e-7,0.01221798,0.002404971,0.00004775804,0.0001106361,0.002328148,4.590624e-7,0.9318815,0.03878221,0.0001999002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[1.920488e-7,0.1679314,0.8216316,0.0002501301,0.001449974,0.006058553,0.002288972,0.00009904188,0.0002901156],"genre_scores_gemma":[2.328419e-7,0.3771264,0.6204691,0.00007244316,0.0007162273,0.001119161,0.00007811776,0.000101954,0.0003163387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8040276,"threshold_uncertainty_score":0.9997454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8358348090652867,"score_gpt":0.6690181020821543,"score_spread":0.1668167069831324,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}